title: Case-only method for cause-specific hazards models with application to assessing differential vaccine efficacy by viral and host genetics.
abstract: Cause-specific proportional hazards models are commonly used for analyzing competing risks data in clinical studies. Motivated by the objective to assess differential vaccine protection against distinct pathogen types in randomized preventive vaccine efficacy trials, we present an alternative case-only method to standard maximum partial likelihood estimation that applies to a rare failure event, e.g. acquisition of HIV infection. A logistic regression model is fit to the counts of cause-specific events (infecting pathogen type) within study arms, with an offset adjusting for the randomization ratio. This formulation of cause-specific hazard ratio estimation permits immediate incorporation of host-genetic factors to be assessed as effect modifiers, an important area of vaccine research for identifying immune correlates of protection, thus inheriting the estimation efficiency, and cost benefits of the case-only estimator commonly used for assessing gene-treatment interactions. The method is used to reassess HIV genotype-specific vaccine efficacy in the RV144 trial, providing nearly identical results to standard Cox methods, and to assess if and how this vaccine efficacy depends on Fc-γ receptor genes.
authors.affiliation: Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
authors.forename: James Y
authors.initials: JY
authors.lastname: Dai
authors.forename: Shuying S
authors.initials: SS
authors.lastname: Li
authors.forename: Peter B
authors.initials: PB
authors.lastname: Gilbert
mesh_terms: D003627:Data Interpretation, Statistical; D005838:Genotype; D006678:HIV / Q000235:genetics / Q000276:immunology; D015658:HIV Infections / Q000517:prevention & control; D006801:Humans; D016013:Likelihood Functions; D016015:Logistic Models
keywords: Gene–treatment interaction; Sieve analysis; Vaccine efficacy